Neurology India, Год журнала: 2023, Номер 71(5), С. 872 - 874
Опубликована: Сен. 1, 2023
Язык: Английский
Cancers, Год журнала: 2023, Номер 15(6), С. 1837 - 1837
Опубликована: Март 18, 2023
An accurate diagnosis of bone tumours on imaging is crucial for appropriate and successful treatment. The advent Artificial intelligence (AI) machine learning methods to characterize assess various modalities may assist in the diagnostic workflow. purpose this review article summarise most recent evidence AI techniques using differentiating benign from malignant lesions, characterization their potential clinical application. A systematic search through electronic databases (PubMed, MEDLINE, Web Science, clinicaltrials.gov) was conducted according Preferred Reporting Items Systematic Reviews Meta-Analyses (PRISMA) guidelines. total 34 articles were retrieved key findings compiled summarised. reported use distinguish between vs. which 12 (35.3%) focused radiographs, MRI, 5 (14.7%) CT PET/CT. overall accuracy, sensitivity, specificity distinguishing lesions ranges 0.44-0.99, 0.63-1.00, 0.73-0.96, respectively, with AUCs 0.73-0.96. In conclusion, discriminate has achieved a relatively good performance modalities, high specificity, accuracy several cohort studies. However, further research necessary test these algorithms before they can be facilitated integrated into routine practice.
Язык: Английский
Процитировано
18
Asian Spine Journal, Год журнала: 2023, Номер 18(1), С. 146 - 157
Опубликована: Дек. 22, 2023
This systematic review summarizes existing evidence and outlines the benefits of artificial intelligence-assisted spine surgery. The popularity intelligence has grown significantly, demonstrating its in computer-assisted surgery advancements spinal treatment. study adhered to PRISMA (Preferred Reporting Items for Systematic Reviews Meta-Analyses), a set reporting guidelines specifically designed reviews meta-analyses. search strategy used Medical Subject Headings (MeSH) terms, including “MeSH (Artificial intelligence),” “Spine” AND “Spinal” filters, last 10 years, English— from January 1, 2013, October 31, 2023. In total, 442 articles fulfilled first screening criteria. A detailed analysis those identified 220 that matched criteria, which 11 were considered appropriate this after applying complete inclusion exclusion studies met eligibility Analysis these revealed types No suggests superiority assisted with or without terms outcomes. feasibility, accuracy, safety, facilitating lower patient radiation exposure compared standard fluoroscopic guidance, produced satisfactory superior incorporation augmented virtual reality appears promising, potential enhance surgeon proficiency overall surgical safety.
Язык: Английский
Процитировано
10
International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 17
Опубликована: Июль 22, 2024
Язык: Английский
Процитировано
3
Cancers, Год журнала: 2024, Номер 16(17), С. 2988 - 2988
Опубликована: Авг. 28, 2024
In spinal oncology, integrating deep learning with computed tomography (CT) imaging has shown promise in enhancing diagnostic accuracy, treatment planning, and patient outcomes. This systematic review synthesizes evidence on artificial intelligence (AI) applications CT for tumors. A PRISMA-guided search identified 33 studies: 12 (36.4%) focused detecting malignancies, 11 (33.3%) classification, 6 (18.2%) prognostication, 3 (9.1%) 1 (3.0%) both detection classification. Of the classification studies, 7 (21.2%) used machine to distinguish between benign malignant lesions, evaluated tumor stage or grade, 2 (6.1%) employed radiomics biomarker Prognostic studies included three that predicted complications such as pathological fractures AI's potential improving workflow efficiency, aiding decision-making, reducing is discussed, along its limitations generalizability, interpretability, clinical integration. Future directions AI oncology are also explored. conclusion, while technologies promising, further research necessary validate their effectiveness optimize integration into routine practice.
Язык: Английский
Процитировано
3
Опубликована: Янв. 1, 2025
Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI
Язык: Английский
Процитировано
0
Опубликована: Март 3, 2025
Процитировано
0
BMC Cancer, Год журнала: 2025, Номер 25(1)
Опубликована: Апрель 15, 2025
Cancer remains a significant health challenge in the ASEAN region, highlighting need for effective screening programs. However, approaches, target demographics, and intervals vary across member states, necessitating comprehensive understanding of these variations to assess program effectiveness. Additionally, while artificial intelligence (AI) holds promise as tool cancer screening, its utilization region is unexplored. This study aims identify evaluate different programs ASEAN, with focus on assessing integration impact AI A scoping review was conducted using PRISMA-ScR guidelines provide overview usage ASEAN. Data were collected from government ministries, official guidelines, literature databases, relevant documents. The use reviews involved searches through PubMed, Scopus, Google Scholar inclusion criteria only included studies that utilized data January 2019 May 2024. findings reveal diverse approaches Countries like Myanmar, Laos, Cambodia, Vietnam, Brunei, Philippines, Indonesia Timor-Leste primarily adopt opportunistic Singapore, Malaysia, Thailand organized Cervical widespread, both methods. Fourteen review, covering breast (5 studies), cervical (2 colon (4 hepatic (1 study), lung oral study) cancers. Studies revealed stages screening: prospective clinical evaluation (50%), silent trial (36%) exploratory model development (14%), promising results enhancing accuracy efficiency. require more targeting appropriate age groups at regular meet WHO's 2030 targets. Efforts integrate Thailand, show optimizing processes, reducing costs, improving early detection. technology enhances identification during detection management region.
Язык: Английский
Процитировано
0
Computers in Biology and Medicine, Год журнала: 2025, Номер 194, С. 110372 - 110372
Опубликована: Июнь 3, 2025
Язык: Английский
Процитировано
0
North American Spine Society Journal (NASSJ), Год журнала: 2023, Номер 15, С. 100236 - 100236
Опубликована: Июнь 20, 2023
Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) widely used clinical decision aids due its ability analyze complex patterns and images. It allows for rapid, enhanced data, imaging analysis, from diagnosis outcome prediction. The purpose of this study was evaluate the current literature utilization DL spine imaging.
Язык: Английский
Процитировано
6
Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 235 - 249
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
2